Foodbot: A goal-oriented just-in-time healthy eating interventions chatbot

• Main Authors: PRASETYO, Philips Kokoh, ACHANANUPARP, Palakorn, LIM, Ee-peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: mHealth; chatbot; diet; self-tracking; food journal; goal-setting; just-in-time intervention; food recommendation; knowledge graph; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5347; https://ink.library.smu.edu.sg/context/sis_research/article/6351/viewcontent/25._Foodbot_A_Goal_Oriented_Just_in_Time_Healthy_Eating_Interventions_Ch....pdf
• Institution: Singapore Management University

Recent research has identified a few design flaws in popular mobile health (mHealth) applications for promoting healthy eating lifestyle, such as mobile food journals. These include tediousness of manual food logging, inadequate food database coverage, and a lack of healthy dietary goal setting. To address these issues, we present Foodbot, a chatbot-based mHealth application for goal-oriented just-in-time (JIT) healthy eating interventions. Powered by a large-scale food knowledge graph, Foodbot utilizes automatic speech recognition and mobile messaging interface to record food intake. Moreover, Foodbot allows users to set goals and guides their behavior toward the goals via JIT notification prompts, interactive dialogues, and personalized recommendation. Altogether, the Foodbot framework demonstrates the use of open-source data, tools, and platforms to build a practical mHealth solution for supporting healthy eating lifestyle in the general population.